Autoimmune and autoinflammatory mechanisms in uveitis

The eye, as currently viewed, is neither immunologically ignorant nor sequestered from the systemic environment. The eye utilises distinct immunoregulatory mechanisms to preserve tissue and cellular function in the face of immune-mediated insult; clinically, inflammation following such an insult is termed uveitis. The intra-ocular inflammation in uveitis may be clinically obvious as a result of infection (e.g. toxoplasma, herpes), but in the main infection, if any, remains covert. We now recognise that healthy tissues including the retina have regulatory mechanisms imparted by control of myeloid cells through receptors (e.g. CD200R) and soluble inhibitory factors (e.g. alpha-MSH), regulation of the blood retinal barrier, and active immune surveillance. Once homoeostasis has been disrupted and inflammation ensues, the mechanisms to regulate inflammation, including T cell apoptosis, generation of Treg cells, and myeloid cell suppression in situ, are less successful. Why inflammation becomes persistent remains unknown, but extrapolating from animal models, possibilities include differential trafficking of T cells from the retina, residency of CD8(+) T cells, and alterations of myeloid cell phenotype and function. Translating lessons learned from animal models to humans has been helped by system biology approaches and informatics, which suggest that diseased animals and people share similar changes in T cell phenotypes and monocyte function to date. Together the data infer a possible cryptic infectious drive in uveitis that unlocks and drives persistent autoimmune responses, or promotes further innate immune responses. Thus there may be many mechanisms in common with those observed in autoinflammatory disorders

Histone Deacetylase Inhibitors Impair the Elimination of HIV-Infected Cells by Cytotoxic T-Lymphocytes

Resting memory CD4+ T-cells harboring latent HIV proviruses represent a critical barrier to viral eradication. Histone deacetylase inhibitors (HDACis), such as suberanilohydroxamic acid (SAHA), romidepsin, and panobinostat have been shown to induce HIV expression in these resting cells. Recently, it has been demonstrated that the low levels of viral gene expression induced by a candidate HDACi may be insufficient to cause the death of infected cells by viral cytopathic effects, necessitating their elimination by immune effectors, such as cytotoxic T-lymphocytes (CTL). Here, we study the impact of three HDACis in clinical development on T-cell effector functions. We report two modes of HDACi-induced functional impairment: i) the rapid suppression of cytokine production from viable T-cells induced by all three HDACis ii) the selective death of activated T-cells occurring at later time-points following transient exposures to romidepsin or, to a lesser extent, panobinostat. As a net result of these factors, HDACis impaired CTL-mediated IFN-γ production, as well as the elimination of HIV-infected or peptide-pulsed target cells, both in liquid culture and in collagen matrices. Romidepsin exerted greater inhibition of antiviral function than SAHA or panobinostat over the dose ranges tested. These data suggest that treatment with HDACis to mobilize the latent reservoir could have unintended negative impacts on the effector functions of CTL. This could influence the effectiveness of HDACi-based eradication strategies, by impairing elimination of infected cells, and is a critical consideration for trials where therapeutic interruptions are being contemplated, given the importance of CTL in containing rebound viremia

The appended curve technique for deconvolutional analysis —method and validation

Deconvolutional analysis (DCA) is useful in correction of organ time activity curves (response function) for variations in blood activity (input function). Despite enthusiastic reports of applications of DCA in renal and cardiac scintigraphy, routine use has awaited an easily implemented algorithm which is insensitive to statistical noise. The matrix method suffers from the propagation of errors in early data points through the entire curve. Curve fitting or constraint methods require prior knowledge of the expected form of the results. DCA by Fourier transforms (FT) is less influenced by single data points but often suffers from high frequency artifacts which result from the abrupt termination of data acquisition at a nonzero value.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46829/1/259_2004_Article_BF00254393.pd

Intelligent Interfaces to Empower People with Disabilities

Severe motion impairments can result from non-progressive disorders, such as cerebral palsy, or degenerative neurological diseases, such as Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), or muscular dystrophy (MD). They can be due to traumatic brain injuries, for example, due to a traffic accident, or to brainste

Adaptace v genetickém programování a symbolické regresi

This paper focuses on the use of hybrid genetic programming for the supervised machine learning method called symbolic regression. While the basic version of GP symbolic regression optimizes both the model structure and its parameters, the hybrid version can use genetic programming to find the model structure. Consequently, local learning is used to tune model parameters. Such tuning of parameters represents the lifetime adaptation of individuals. Choice of local learning method can accelerate the evolution, but it also has its disadvantages in the form of additional costs. Strong local learning can inhibit the evolutionary search for the optimal genotype due to the hiding effect, in which the fitness of the individual only slightly depends on his inherited genes. This paper aims to compare the Lamarckian and Baldwinian approaches to the lifetime adaptation of individuals and their influence on the rate of evolution in the search for function, which fits the given input-output data.Tento článek se zaměřuje na použití hybridního genetického programování pro symbolickou regresi Hybridní verze symbolické regrese používá genetické programování pro hledání struktury matematického modelu a lokální učení pro ladění parametrů modelu. Lokálního učení může urychlit evoluci, ale nevýhodou jsou dodatečné výpočetní náklady. Článek porovnává Lamarckův a Baldwinův přístup k evoluci a jejich vliv na umělou evoluci při hledání matematického modelu popisujícího zadané datové body

Photobook: Content-Based Manipulation of Image Databases

We describe the Photobook system, which is a set of interactive tools for browsing and searching images and image sequences. These query tools differ from those used in standard image databases in that they make direct use of the image content rather than relying on text annotations. Direct search on image content is made possible by use of semantics-preserving image compression, which reduces images to a small set of perceptually-significant coefficients. We describe three types of Photobook descriptions in detail: one that allows search based on appearance, one that uses 2-D shape, and a third that allows search based on textural properties. These image content descriptions can be combined with each other and with textbased descriptions to provide a sophisticated browsing and search capability. In this paper we demonstrate Photobook on databases containing images of people, video keyframes, hand tools, fish, texture swatches, and 3-D medical data